Current camera technology typically limits image capture possibilities to very specific conditions in which an image of acceptable quality can be produced. As a result of this limitation, several camera settings need to be appropriately chosen before an image of optimal quality can be taken. Cameras have long had the ability to assess the scene conditions and automatically adjust settings such as: exposure time, iris/lens aperture, focus, sensor gain, and the use of neutral density filters. While film-based cameras have traditionally relied on external measuring sensors to select these settings, modern compact digital cameras make use of several through-the-lens measurements that provide image-based data to automatically adjust settings through algorithms that compare these measurements and decide on optimal settings.
The mechanism of exposure provides adjustment of the device sensitivity to the light intensity in the scene. This is in part motivated by the limited dynamic range (ratio of highest to lowest light intensity) of the camera system compared to the dynamic range of intensities in the real world. In an imaging capture device, a metering and auto-exposure algorithm finds optimal values for the above parameters (some of these parameters may be specified or fixed). An auto-exposure algorithm aims to find the optimal exposure settings for the camera system by modifying a subset of the following parameters: exposure time, iris/lens aperture, sensor gain, and the use of neutral density filters.
Cameras equipped with auto-focus lens can generally capture an image of acceptable quality at a certain focus setting, while relying on an auto-focus algorithm to select the accurate focus position where the chosen parts of the image are considered to be acceptably sharp. In a traditional compact digital camera, auto-focus can be achieved by capturing successive images (or selected regions of interest in successive images) at varying focus positions through “focus sweep” and selecting the setting corresponding to the image (or selected regions of interest in the image) of best “focus”. An auto-focus algorithm aims to find the optimal focus setting for the camera system. The auto-exposure and auto-focus functions in digital cameras share the characteristic that they both generally rely on taking multiple measurements in order to estimate the best camera settings prior to actual image capture.
Auto-exposure algorithms may rely on external light meters/sensors or may evaluate optimal exposure time through the lens by successive image capturing as described above. In many legacy cameras auto-exposure algorithms run concurrently with image preview mode. Due to the fact that preview mode provides real time video, the auto-exposure algorithm is typically configured to make small adjustments in the exposure time since changes in exposure are immediately visible in the preview video. These small adjustments result in delays in identifying optimal exposure times.
Autofocus is another feature that generally runs when the device is in preview mode. Again, since image preview mode provides real time video, the autofocus process typically involves gradually varying the focus point in a slow sweep. Although there are multiple approaches to performing autofocus (including phase detection that uses dedicated focusing sensors), methods appropriate for compact cameras typically involve capturing several images and analyzing the captured images for parameters such as contrast or blur amount. Such autofocus methods, along with slow sweep, can also result in delays.
The High Dynamic Range (HDR) feature provides a means to produce images that convey higher dynamic range (higher ratio of intensities corresponding to light and dark areas in image). In a conventional image capture mode (i.e. one that does not involve capturing HDR information), images are traditionally captured at one exposure level (may vary for each color channel in architectures allowing this). The camera system's dynamic range is typically limited by several factors, including the finite number of bits in the analog-to-digital converters, reduced full-well sensor capacity as well as optical characteristics. HDR mode utilizes a set of methods that sample a scene's dynamic range more aggressively by capturing multiple images of the scene at different exposure levels. Each exposure creates brackets of smaller or regular dynamic range that can be sampled to produce a composite image of high (increased) dynamic range. Various blending models and/or algorithms can be utilized to create a single HDR image from the multiple images. The High Dynamic Range mode typically includes two steps: High Dynamic Range capture and High Dynamic Range Image Blending and Compression. In the High Dynamic Range capture step, multiple images may be captured at a pre-defined difference in exposure setting from the reference exposure; for example, if the reference exposure is EV0, an image with a smaller exposure by a factor of 2 may be captured and an image with a greater exposure by a factor of 2 may be captured as following: EV0, EV−1 (short exposure), EV+1 (long exposure). (Note: numbers follow the exposure value convention and correspond to base-2 logarithmic scale such that EV−1 corresponds to half of EV0 exposure, EV+1 corresponds to double the EV0 exposure).